~( Ferret Knots )~

Jan 27, 2007

2007 week 05: Articles in Proteins

Getting one's protein in a bunch -- When quality control fails in cellsOver time, a relatively minor mistake in protein production at the cellular level may lead to serious neurological diseases. But exactly how the cell avoids such mistakes has remained unclear until now. Researchers at Ohio State University found the mechanism that prevents such errors, and explain their findings in the Proceedings of the National Academy of Sciences.

Quantum biology -- Powerful computer models reveal key biological mechanismTroy, N.Y. -- Using powerful computers to model the intricate dance of atoms and molecules, researchers at Rensselaer Polytechnic Institute have revealed the mechanism behind an important biological reaction. In collaboration with scientists from the Wadsworth Center of the New York State Department of Health, the team is working to harness the reaction to develop a "nanoswitch" for a variety of applications, from targeted drug delivery to genomics and proteomics to sensors.The research is part of a burgeoning discipline called "quantum biology," which taps the skyrocketing power of today's high-performance computers to precisely model complex biological processes. The secret is quantum mechanics -- the much-touted theory from physics that explains the inherent "weirdness" of the atomic realm.

Microtubule protein interactions visualized en masseIn a new study published online in the open access journal PLoS Biology, Philipp Niethammer, Eric Karsenti, and colleagues investigate the regulation of microtubule dynamics via application of their new method, called visual immunoprecipitation (VIP), which enables simultaneous visualization of multiple protein interactions in cell extracts.

2007 week 05: Articles of Related Interest

Chopping Off Protein Puts Immune Cells Into High GearThe complex task of launching a well-organized, effective immune system attack on specific targets is thrown into high gear when either of two specific enzymes chop a protein called LAG-3 off the immune cells leading that battle, according to investigators at St. Jude Children's Research Hospital.

Role For Proteomics In Identifying Hematologic MalignanciesScientists have identified a set of biomarkers that could help clinicians identify a group of hematologic malignancies known as myelodysplastic syndromes (MDS), which affect approximately 300,000 individuals worldwide and often progress to acute myeloid leukemia.

Motor protein plays key role in connecting neuronsA motor protein called myosin X runs the main road of a developing neuron, delivering to its tip a receptor that enables it to communicate with other neurons, scientists say. In another piece of the puzzle of how neurons form connections, researchers have found myosin X travels a portion of a neuron's backbone called the actin filament, a sort of two-way highway in the cell's highest traffic area, says Dr. Wen-Cheng Xiong, developmental neurobiologist at the Medical College of Georgia.

'Quiet Revolution' May Herald New RNA TherapeuticsScientists at the University of Oxford have identified a surprising way of switching off a gene involved in cell division. The mechanism involves a form of RNA, a chemical found in cell nuclei, whose role was previously unknown, and could have implications for preventing the growth of tumour cells.RNA plays an important and direct role in the synthesis of proteins, the building blocks of our bodies. However, scientists have known for some time that not all types of RNA are directly involved in protein synthesis. Now, in research funded by the Wellcome Trust and the Medical Research Council, a team of scientists has shown that one particular type of RNA plays a key role in regulating the gene implicated in control of tumour growth. The research is published online today in Nature.

Chemical Switch Triggers Critical Cell ActivitiesThe freeze-frame image of a molecular relay race, in which one enzyme passes off a protein like a baton to another enzyme, has solved a key mystery to how cells control some vital functions, according to investigators at St. Jude Children's Research Hospital. A report on this work appears in the January 14 advanced online publication issue of Nature.

Buckyballs used as 'passkey' into cancer cellsRice University chemists and Baylor College of Medicine pediatric scientists have discovered how to use buckyballs as passkeys that allows drugs to enter cancer cells. Research in the January 21 issue of the journal Organic and Biomolecular Chemistry, describes how the researchers mimicked the techniques used by some viruses to introduce non-toxic bits of buckyball-containing protein into both neuroblastoma and liver cancer cells.

Filamins Tether Cystic Fibrosis Protein To Cell SurfaceCystic fibrosis (CF) is caused by mutations in a gene that encodes a protein known as CFTR. More than 1000 different disease-causing mutations in CFTR have been identified, and although the overall effect of each mutation is to decrease CFTR expression at the cell surface, it is not known for every one of these mutations what the molecular defect is that causes the decreased cell surface expression of CFTR.From the article itself: "Our data demonstrate what we believe to be a previously unrecognized role for the CFTR N terminus in the regulation of the plasma membrane stability and metabolic stability of CFTR. In addition, we elucidate the molecular defect associated with the S13F mutation."

Breakthrough Could Prevent Multiple Fibrotic Diseases: Tests Find Protein Stops Fibrosis In Lung, Heart, Other Tissues Science DailyA scientific breakthrough at Rice University could lead to the first treatment that prevents the build-up of deadly scar tissue in a broad class of diseases that account for an estimated 45 percent of U.S. deaths each year."Fibrotic diseases kill so many people because they can crop up in almost any part of the body, and cardiac fibrosis is a particular problem for anyone who's had a heart attack," said Richard Gomer, professor of biochemistry and cell biology at Rice. "We've discovered a naturally occurring blood protein that prevents dangerous scar tissue from forming."

Brown team finds crucial protein role in deadly prion spreadBrown University biologists have made another major advance toward understanding the deadly work of prions, the culprits behind fatal brain diseases such as mad cow and their human counterparts. In new work published online in PLoS Biology, researchers show that the protein Hsp104 must be present and active for prions to multiply and cause disease.

2007 week 05: Articles in Maths

Statistical Method Used Influences Results Of Observational StudiesA study comparing different statistical methods used to remove the effects of selection bias in observational studies finds that results may vary and caution may be warranted when interpreting findings of studies using certain methods, according to an article in the January 17 issue of JAMA."Randomized clinical trials cannot be undertaken in all situations in which evidence is needed to guide care. Well-designed observational studies are still needed to assess population effectiveness and to extend results to a general population setting. Our study serves as a cautionary note regarding their analysis and interpretation. First, propensity scores and propensity-based matching have the same limitations as multivariable risk adjustment model methods, and are no more likely to remove bias due to unmeasured confounding when strong selection bias exists. Second, instrumental variable analyses may remove both overt and hidden biases but are more suited to answer policy questions than to provide insight into a specific clinical question for a specific patient. Caution is advised regarding clinical protocols and policy statements for invasive care based on expected mortality benefits derived from traditional multivariable modeling and propensity score risk adjustment of observational studies," the researchers conclude.Note: This story has been adapted from a news release issued by JAMA and Archives Journals.

Microlocal AnalysisIn mathematical analysis, microlocal analysis is a term use to describe techniques developed from the 1950s onwards based on Fourier transforms related to the study of variable-coefficients-linear and nonlinear partial differential equations. This includes generalized functions, pseudo-differential operators, wave front sets, Fourier integral operators, and paradifferential operators.The term microlocal implies localisation not just at a point, but in terms of cotangent space directions at a given point. This gains in importance on manifolds of dimension greater than one.This entry was adapted from the Wikipedia article Microlocal analysis as of January 17, 2007.

The articles below contains text in the LaTex format. To view the article correctly, please visit the source link.

Fuzzy SubsetFuzzy set theory is based on the idea that vague notions as "big", "near", "hold" can be modelled by "fuzzy subsets". A fuzzy subset of a set S is a map ... from S into the interval ... . More precisely, the interval ... is considered as a complete lattic ...

Eventual PropertyLet be a set and a property on the elements of . Let be a net ( a directed set) in (that is, ). As each , either has or does not have property . We say that the net has property above if has property for all . Furthermore, we say that eventually has property if it has property above some .

Partial Ordering In A Topological SpaceLet X be a T0 space. For any ... , we define a binary relation le as follows: ... Proposition . The binary relation just defined is a partial order. ... Clearly ... . Suppose next that ... and ... . If ... , then there is an open set A such that ... and . ...

Jan 13, 2007

2007 week 03: Articles in Proteins

Spanish Scientists Reveal Dynamic Map Of Proteins, Possibilities For New DrugsScientists from the Institute for Research in Biomedicine (IRB Barcelona), the Life Sciences Programme at the Barcelona Supercomputing Center (BSC) and the National Institute for Bioinformatics (INB) have published a provisional "atlas" of the dynamic behaviour of proteins in the prestigious scientific journal, Proceedings of the National Academy of Sciences USA.

Proteins determine the shape and structure of cells and drive nearly all of a cell's vital processes. All proteins carry out their functions according to the same process -- by binding with other molecules. Now, the scientists have compiled a map that shows them how proteins can move and form complexes, a valuable tool that will help them understand the basic functions of the molecules, but also what happens when they function incorrectly. Such a map opens vast possibilities for the design of new drugs.

The goal of this study is to define a map of the dynamic properties of a very representative group of proteins. This involves taking stock of the basic rules that govern the flexibility of proteins and allows scientists to predict the structures that these proteins can form based on the presence of ligands or modifications. This allows scientists to go beyond the traditional simple static vision of proteins, which has not been able to capture the subtle conformational changes necessary for proteins to function. These changes modify, for example, how proteins bind to metabolites or drugs....This is the first study of a larger scientific project, called MoDel (Molecular Dynamics Extended Library), the scope of which is even more ambitious. "MoDel aims to establish a 'fourth dimension' for protein structures thereby providing a complete landscape of possible conformations for the entire proteome (the complete network of protein interactions in a cell), over time. In the near future, a biochemist will be able to understand the behaviour of a protein, or design a drug that can interact with that protein, drawing on not only the knowledge of a single structure, but of an entire repertory spontaneously occurring in physiological conditions," says project director Modesto Orozco, principal investigator of the Molecular Modelling and Bioinformatics group at IRB Barcelona, director of the Department of Life Sciences of the BSC, and Professor in the Department of Biochemistry at the University of Barcelona....Source article: M.Rueda, C.Ferrer, T.Meyer, A.Pérez, J.Camps, A.Hospital, J.L.Gelpí and M.Orozco. "A consensus view of protein dynamics". Proc. Natl. Acad. Sci. USA. (2007) 104, 796-801

Science's breakthrough of the year -- The Poincaré TheoremScience honors the top 10 research advances of 2006In 2006, researchers closed a major chapter in mathematics, reaching a consensus that the elusive Poincaré Conjecture, which deals with abstract shapes in three-dimensional space, had finally been solved. Science and its publisher AAAS, the nonprofit society, now salute this development as the Breakthrough of the Year and also give props to nine other of the year’s most significant scientific accomplishments....The Poincaré Conjecture is part of a branch of mathematics called topology, informally known as "rubber sheet geometry" because it involves surfaces that can undergo arbitrary amounts of stretching. The conjecture, proposed in 1904 by Henri Poincaré, describes a test for showing that a space is equivalent to a "hypersphere," the three-dimensional surface of a four-dimensional ball.

Partial least squares: a versatile tool for the analysis of high-dimensional genomic dataPartial least squares (PLS) is an efficient statistical regression technique that is highly suited for the analysis of genomic and proteomic data. In this article, we review both the theory underlying PLS as well as a host of bioinformatics applications of PLS. In particular, we provide a systematic comparison of the PLS approaches currently employed, and discuss analysis problems as diverse as, e.g. tumor classification from transcriptome data, identification of relevant genes, survival analysis and modeling of gene networks and transcription factor activities.

Multivariate Distribution FunctionMultivariate distribution functions are typically found in probability theory, and especially in statistics. An example of a commonly used multivariate distribution function is the multivariate Gaussian distribution function....The attempt here is to study a class of functions that can be used as models for distributions of distances between points in a “probabilistic metric space”.

2007 week 03: Articles of Related Interest

Finding Patterns Of Importance In A Deluge Of DataScience Daily — Dartmouth engineers George Cybenko and Vincent Berk think that PQS, or process query systems, are the way to go to make sense of the huge volume of data we collect each day... The duo present their case in a paper published in this month's IEEE Computer, the flagship magazine of the Institute of Electrical and Electronics Engineers' Computer Society....According to Cybenko, "PQS can do for discrete, categorical data analysis problems what classical times series analysis did for finance and control systems where the data are numerical."

Jan 3, 2007

2007 week 01: Articles in Veterinary Science

Isolation of ferret protein promising for cancer, reproductive studiesAlthough the focus of the study was about pregnancy, there was this interesting general finding.Clip:The protein -- glucose-6-phosphate isomerase (GPI) -- already is widely known as a highly conserved enzyme occurring in intracellular metabolism, converting sugars in glycolysis in many organisms and humans. "In the domestic ferrets that we studied, we found a unique role for this enzyme as a secreted protein that is essential in the reproductive process," Bahr said. "Interestingly, he same ability to secrete this protein is found in many types of metastatic tumors, suggesting that tumor cells have co-opted this process. The secretion of GPI allows the tumors to find and lock onto receptors to invade healthy tissues." The ability of tumors to spread is similar to the invasive process of implantation.

Jan 2, 2007

2007 week 01: Articles of Related Interest

Bacterial resistance to antibiotics is a major challenge for the current treatment of infectious diseases. One way bacteria can escape destruction is by pumping out administered drugs through specific transporter proteins that span the cell membrane, such as AcrB.

The U.S. Department of Agriculture's Agricultural Research Service have announced initial results of a research project involving prion-free cattle. ARS scientists evaluated cattle that have been genetically modified so they do not produce prions, and determined that there were no observable adverse effects on the animals' health.

Computer scientists at the University of California, San Diego, and Brown University have created a software system that more accurately detects "microinversions," mutations that consist of tiny sequences of reversed DNA. The software gives biologists a powerful new tool to study genomic variation between and within species. The system is explained in the online edition of the Proceedings of the National Academy of Sciences.

2007 week 01: Articles in General Medicine

USC researchers have determined the 3-D atomic structure of the Apo2 protein, the first of the APOBEC enzyme family to be described. The protein structure has guided them to a new understanding of what goes wrong on a molecular level in a rare, but serious immunodeficiency syndrome.

We report the first high-resolution structure for a protein containing a fluorinated side chain... Our findings are important because they complement several studies that have shown that fluorination of saturated side chain carbon atoms can provide enhanced conformational stability.

We exploit the availability of recent experimental data on a variety of proteins to develop a Web-based prediction algorithm (BPPred) to calculate several biophysical parameters commonly used to describe the folding process. These parameters include the equilibrium m-values, the length of proteins, and the changes upon unfolding in the solvent-accessible surface area, in the heat capacity, and in the radius of gyration. We also show that the knowledge of any one of these quantities allows an estimate of the others to be obtained, and describe the confidence limits with which these estimations can be made. Furthermore, we discuss how the kinetic m-values, or the Beta Tanford values, may provide an estimate of the solvent-accessible surface area and the radius of gyration of the transition state for protein folding. Taken together, these results suggest that BPPred should represent a valuable tool for interpreting experimental measurements, as well as the results of molecular dynamics simulations.

2007 week 01: Articles in Maths

In systems biology, biologically relevant quantitative modelling of physiological processes requires the integration of experimental data from diverse sources. Recent developments in high-throughput methodologies enable the analysis of the transcriptome, proteome, interactome, metabolome and phenome on a previously unprecedented scale, thus contributing to the deluge of experimental data held in numerous public databases. In this review, we describe some of the databases and simulation tools that are relevant to systems biology and discuss a number of key issues affecting data integration and the challenges these pose to systems-level research.

Modelers of molecular interaction networks encounter the paradoxical situation that while large amounts of data are available, these are often insufficient for the formulation and analysis of mathematical models describing the network dynamics. In particular, information on the reaction mechanisms and numerical values of kinetic parameters are usually not available for all but a few well-studied model systems. In this article we review two strategies that have been proposed for dealing with incomplete information in the study of molecular interaction networks: parameter sensitivity analysis and model simplification. These strategies are based on the biologically justified intuition that essential properties of the system dynamics are robust against moderate changes in the value of kinetic parameters or even in the rate laws describing the interactions. Although advanced measurement techniques can be expected to relieve the problem of incomplete information to some extent, the strategies discussed in this article will retain their interest as tools providing an initial characterization of essential properties of the network dynamics.

Systems biology applies quantitative, mechanistic modelling to study genetic networks, signal transduction pathways and metabolic networks. Mathematical models of biochemical networks can look very different. An important reason is that the purpose and application of a model are essential for the selection of the best mathematical framework. Fundamental aspects of selecting an appropriate modelling framework and a strategy for model building are discussed.

Concepts and methods from system and control theory provide a sound basis for the further development of improved and dedicated computational tools for systems biology. Identification of the network components and rate constants that are most critical to the output behaviour of the system is one of the major problems raised in systems biology. Current approaches and methods of parameter sensitivity analysis and parameter estimation are reviewed. It is shown how these methods can be applied in the design of model-based experiments which iteratively yield models that are decreasingly wrong and increasingly gain predictive power.

We find accurate approximations for the expected number of three-cycles and unchorded four-cycles under a stochastic distribution for graphs that has been proposed for modelling yeast two-hybrid protein–protein interaction networks. We show that unchorded four-cycles are characteristic motifs under this model and that the count of unchorded four-cycles in the graph is a reliable statistic on which to base parameter estimation. Finally, we test our model against a range of experimental data, obtain parameter estimates from these data and investigate possible improvements in the model. Characterization of this model lays the foundation for its use as a prior distribution in a Bayesian analysis of yeast two-hybrid networks that can potentially aid in identifying false-positive and false-negative results.

A two-channel microarray measures the relative expression levels of thousands of genes from a pair of biological samples. In order to reliably compare gene expression levels between and within arrays, it is necessary to remove systematic errors that distort the biological signal of interest. The standard for accomplishing this is smoothing "MA-plots" to remove intensity-dependent dye bias and array-specific effects. However, MA methods require strong assumptions, which limit their general applicability. We review these assumptions and derive several practical scenarios in which they fail. The "dye-swap" normalization method has been much less frequently used because it requires two arrays per pair of samples. We show that a dye-swap is accurate under general assumptions, even under intensity-dependent dye bias, and that a dye-swap removes dye bias from a single pair of samples in general. Based on a flexible model of the relationship between mRNA amount and single-channel fluorescence intensity, we demonstrate the general applicability of a dye-swap approach. We then propose a common array dye-swap (CADS) method for the normalization of two-channel microarrays. We show that CADS removes both dye bias and array-specific effects, and preserves the true differential expression signal for every gene under the assumptions of the model.

In this paper, we introduce a modified version of linear discriminant analysis, called the "shrunken centroids regularized discriminant analysis" (SCRDA). This method generalizes the idea of the "nearest shrunken centroids" (NSC) (Tibshirani and others, 2003) into the classical discriminant analysis. The SCRDA method is specially designed for classification problems in high dimension low sample size situations, for example, microarray data. Through both simulated data and real life data, it is shown that this method performs very well in multivariate classification problems, often outperforms the PAM method (using the NSC algorithm) and can be as competitive as the support vector machines classifiers. It is also suitable for feature elimination purpose and can be used as gene selection method. The open source R package for this method (named "rda") is available on CRAN (http://www.r-project.org) for download and testing.

In many microarray studies, a cluster defined on one dataset is sought in an independent dataset. If the cluster is found in the new dataset, the cluster is said to be "reproducible" and may be biologically significant. Classifying a new datum to a previously defined cluster can be seen as predicting which of the previously defined clusters is most similar to the new datum. If the new data classified to a cluster are similar, molecularly or clinically, to the data already present in the cluster, then the cluster is reproducible and the corresponding prediction accuracy is high. Here, we take advantage of the connection between reproducibility and prediction accuracy to develop a validation procedure for clusters found in datasets independent of the one in which they were characterized. We define a cluster quality measure called the "in-group proportion" (IGP) and introduce a general procedure for individually validating clusters. Using simulations and real breast cancer datasets, the IGP is compared to four other popular cluster quality measures (homogeneity score, separation score, silhouette width, and weighted average discrepant pairs score). Moreover, simulations and the real breast cancer datasets are used to compare the four versions of the validation procedure which all use the IGP, but differ in the way in which the null distributions are generated. We find that the IGP is the best measure of prediction accuracy, and one version of the validation procedure is the more widely applicable than the other three. An implementation of this algorithm is in a package called "clusterRepro" available through The Comprehensive R Archive Network.

Welcome Mathematicians and Ferret-Lovers!

Welcome!

This brain-child was first spontaneously conceived at the end of 2006, but the full-blown birth occurred in 2007, ringing in the New Year of the Boar!!

What We Are Doing:As the subtitle says, we're a group of interested people looking to apply maths in the quest to find solutions in veterinary science. Historically, a majority of applied mathematics has been used to study human aliments; we wish now to turn our focus to other equally worthy endeavors - our companion animals.

What Can You Expect To See Here:We'll be posting links, articles, conjectures and information from all the relevant maths and veterinary sciences to help us further our goal. The most commonly applied maths addressed will be in the fields of dynamics, topology, biomathematics, and biostatistics.

ALERTS

UPDATING PROCESS HAS BEGUN!!
Thanks for your patience! ^.^

Articles & LOTS of links have been updated. More to come!Discussion Board Opened HERE in FEB. 2007!

*We're mostly settled in, but still working the kinks out in the articles. For example, I can't decide how to categorize all the protein articles--should protein structure, protein folding, general protein articles, etc... be completely seperate or partially grouped or...? That type of problem.

About These Articles

some of the articles here are free to the public, others can be bought through the respective sites, and still others require you to be a member of that society, eg some AVMA articles.

Links - General Science

PubMed:
Search all sorts of DB's for the latest research published in the US. Freely accessible to all.

Discussion Board

A place to debate your ideas, discuss the articles, and share information.
Opened HERE in Feb. 2007

Actually, I expect it to be rather quiet, mostly functioning as our own private notepad or a message board for those who find the public message board below too cramped. At any rate, it's available for posting and chatting! You just need to join the forum.